



import os
from typing import List, Optional, Union

from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging


a      :  int			     =			logging.get_logger(__name__)

a      :  str			     =			{'vocab_file': 'vocab.txt'}

a      :  Any			     =			{
    'vocab_file': {
        'facebook/esm2_t6_8M_UR50D': 'https://huggingface.co/facebook/esm2_t6_8M_UR50D/resolve/main/vocab.txt',
        'facebook/esm2_t12_35M_UR50D': 'https://huggingface.co/facebook/esm2_t12_35M_UR50D/resolve/main/vocab.txt',
    },
}

a      :  str			     =			{
    'facebook/esm2_t6_8M_UR50D': 1_024,
    'facebook/esm2_t12_35M_UR50D': 1_024,
}







def  lowerCAmelCase_	(lowerCAmelCase__:		List[str]  ):





			"""simple docstring"""


			with open(lowerCAmelCase__		,						"""r"""  ) as f:
						UpperCAmelCase_:		Tuple							      =     f.read().splitlines()
						return [l.strip() for l in lines]







class 				_a				(   _lowerCAmelCase					):
			A      		=	VOCAB_FILES_NAMES
			A      		=	PRETRAINED_VOCAB_FILES_MAP
			A      		=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			A      		=	['''input_ids''', '''attention_mask''']

			def __init__(self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_="<unk>",   SCREAMING_SNAKE_CASE_="<cls>",   SCREAMING_SNAKE_CASE_="<pad>",   SCREAMING_SNAKE_CASE_="<mask>",   SCREAMING_SNAKE_CASE_="<eos>",   **SCREAMING_SNAKE_CASE_,   )       ->   Optional[int]:
						super().__init__(**SCREAMING_SNAKE_CASE_					)
						UpperCAmelCase_:		Optional[int]							      =     load_vocab_file(SCREAMING_SNAKE_CASE_					)
						UpperCAmelCase_:		List[str]							      =     dict(enumerate(self.all_tokens					)					)
						UpperCAmelCase_:		Union[str, Any]							      =     {tok: ind for ind, tok in enumerate(self.all_tokens					)}
						UpperCAmelCase_:		str							      =     unk_token
						UpperCAmelCase_:		List[str]							      =     cls_token
						UpperCAmelCase_:		Dict							      =     pad_token
						UpperCAmelCase_:		Optional[int]							      =     mask_token
						UpperCAmelCase_:		Dict							      =     eos_token
						UpperCAmelCase_:		Tuple							      =     self.all_tokens
						self._create_trie(self.unique_no_split_tokens					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   str:
						return self._id_to_token.get(SCREAMING_SNAKE_CASE_,   self.unk_token					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   int:
						return self._token_to_id.get(SCREAMING_SNAKE_CASE_,   self._token_to_id.get(self.unk_token					)					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   **SCREAMING_SNAKE_CASE_					)       ->   List[str]:
						return text.split()

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_=False					)       ->   Union[str, Any]:
						return len(self._id_to_token					)

			def      __snake_case       (self					)       ->   Optional[Any]:
						return {token: i for i, token in enumerate(self.all_tokens					)}

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   int:
						return self._token_to_id.get(SCREAMING_SNAKE_CASE_,   self._token_to_id.get(self.unk_token					)					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   str:
						return self._id_to_token.get(SCREAMING_SNAKE_CASE_,   self.unk_token					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None					)       ->   List[int]:
						UpperCAmelCase_:		int							      =     [self.cls_token_id]
						UpperCAmelCase_:		str							      =     [self.eos_token_id]  # No sep token in ESM vocabulary
						if token_ids_a is None:
									if self.eos_token_id is None:
												return cls + token_ids_a
									else:
												return cls + token_ids_a + sep
						elif self.eos_token_id is None:
									raise ValueError("""Cannot tokenize multiple sequences when EOS token is not set!"""					)
						return cls + token_ids_a + sep + token_ids_a + sep  # Multiple inputs always have an EOS token

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None,   SCREAMING_SNAKE_CASE_ = False					)       ->   List[int]:
						if already_has_special_tokens:
									if token_ids_a is not None:
												raise ValueError(
												    """You should not supply a second sequence if the provided sequence of """
												    """ids is already formatted with special tokens for the model."""					)

									return [1 if token in self.all_special_ids else 0 for token in token_ids_a]
						UpperCAmelCase_:		List[Any]							      =     [1] + ([0] * len(SCREAMING_SNAKE_CASE_					)) + [1]
						if token_ids_a is not None:
									mask += [0] * len(SCREAMING_SNAKE_CASE_					) + [1]
						return mask

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_					)       ->   Union[str, Any]:
						UpperCAmelCase_:		Tuple							      =     os.path.join(SCREAMING_SNAKE_CASE_,   (filename_prefix + """-""" if filename_prefix else """""") + """vocab.txt"""					)
						with open(SCREAMING_SNAKE_CASE_,   """w"""					) as f:
									f.write("""\n""".join(self.all_tokens					)					)
						return (vocab_file,)

			@property
			def      __snake_case       (self					)       ->   int:
						return self.get_vocab_size(with_added_tokens=SCREAMING_SNAKE_CASE_					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = False					)       ->   int:
						return super()._add_tokens(SCREAMING_SNAKE_CASE_,   special_tokens=SCREAMING_SNAKE_CASE_					)











import numpy as np







def  lowerCAmelCase_	(lowerCAmelCase__:		np.ndarray		,						lowerCAmelCase__:		float  ):





			"""simple docstring"""


			return np.where(vector > 0		,						lowerCAmelCase__		,						(alpha * (np.exp(lowerCAmelCase__  ) - 1))  )


if __name__ == "__main__":
	import doctest

	doctest.testmod()






